Credit Mastery

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name: swarms-ai description: Build and orchestrate multi-agent AI systems using the Swarms API. Use when creating single agents, multi-agent swarms (sequential, concurrent, hierarchical, mixture-of-agents, majority voting, graph workflows), launching agent tokens on Solana, integrating ATP payment protocol, publishing to Swarms Marketplace, using sub-agent delegation, streaming responses, or building any multi-agent orchestration pipeline. Covers Python, TypeScript, and cURL.

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Swarms AI — Multi-Agent Orchestration

Build production-grade multi-agent systems using the Swarms API platform. Supports single agents, reasoning agents, and swarms of 3–10,000+ agents with 20+ architecture patterns.

Quick Reference

Base URL: https://api.swarms.world

Auth: x-api-key header with API key from swarms.world/platform/api-keys

Docs index: https://docs.swarms.ai/llms.txt

Python SDK: pip install swarms-client

Marketplace: swarms.world

Architecture Tiers

| Tier | Name | Agents | Endpoint | |------|------|--------|----------| | 1 | Individual Agent | 1 | /v1/agent/completions | | 2 | Reasoning Agent | 1-2 internal | /v1/reasoning-agent/completions | | 3 | Multi-Agent Swarm | 3–10,000+ | /v1/swarm/completions |

Workflow

1. Single Agent

import requests
payload = {
    "agent_config": {
        "agent_name": "MyAgent",
        "description": "Purpose of the agent",
        "system_prompt": "You are...",
        "model_name": "gpt-4o",  # or claude-sonnet-4-20250514, etc.
        "role": "worker",
        "max_loops": 1,
        "max_tokens": 8192,
        "temperature": 0.5,
        "auto_generate_prompt": False,
        "tools_list_dictionary": None
    },
    "task": "Your task here"
}
response = requests.post(
    "https://api.swarms.world/v1/agent/completions",
    headers={"x-api-key": API_KEY, "Content-Type": "application/json"},
    json=payload
)

2. Multi-Agent Swarm

payload = {
    "name": "My Swarm",
    "description": "What this swarm does",
    "agents": [
        {
            "agent_name": "Agent1",
            "description": "Role 1",
            "system_prompt": "You are...",
            "model_name": "gpt-4o",
            "role": "worker",
            "max_loops": 1,
            "max_tokens": 8192,
            "temperature": 0.5
        },
        {
            "agent_name": "Agent2",
            "description": "Role 2",
            "system_prompt": "You are...",
            "model_name": "claude-sonnet-4-20250514",
            "role": "worker",
            "max_loops": 1,
            "max_tokens": 8192,
            "temperature": 0.5
        }
    ],
    "max_loops": 1,
    "swarm_type": "SequentialWorkflow",  # See architecture table
    "task": "Your task here"
}
response = requests.post(
    "https://api.swarms.world/v1/swarm/completions",
    headers={"x-api-key": API_KEY, "Content-Type": "application/json"},
    json=payload
)

3. Token Launch (Solana)

payload = {
    "name": "My Agent Token",
    "description": "Agent description",
    "ticker": "MAG",
    "private_key": "[1,2,3,...]"  # Solana wallet private key
}
response = requests.post(
    "https://swarms.world/api/token/launch",
    headers={"Authorization": "Bearer API_KEY", "Content-Type": "application/json"},
    json=payload
)
Returns: token_address, pool_address, listing_url
Cost: ~0.04 SOL

Available Swarm Architectures

Use the swarm_type parameter:

| Type | Description | Best For | |------|-------------|----------| | SequentialWorkflow | Linear pipeline, each agent builds on previous | Step-by-step processing | | ConcurrentWorkflow | Parallel execution | Independent tasks, speed | | AgentRearrange | Dynamic agent reordering | Adaptive workflows | | MixtureOfAgents | Specialist agent selection | Multi-domain tasks | | MultiAgentRouter | Intelligent task routing | Large-scale distribution | | HierarchicalSwarm | Nested hierarchies with delegation | Complex org structures | | MajorityVoting | Consensus across agents | Decision making | | BatchedGridWorkflow | Grid pattern execution | Multi-task × multi-agent | | GraphWorkflow | Directed graph of agent nodes | Complex dependencies | | GroupChat | Agent discussion | Collaborative brainstorming | | InteractiveGroupChat | Real-time agent interaction | Dynamic collaboration | | AutoSwarmBuilder | Auto-generate optimal swarm | When unsure of architecture | | HeavySwarm | High-capacity processing | Large workloads | | DebateWithJudge | Structured debate | Adversarial evaluation | | RoundRobin | Round-robin distribution | Even load distribution | | MALT | Multi-agent learning | Training systems | | CouncilAsAJudge | Expert panel evaluation | Quality assessment | | LLMCouncil | LM council for decisions | Group decision making | | AdvancedResearch | Research workflows | Deep research | | auto | Auto-select best type | Default/unknown |

Agent Config Parameters

| Param | Type | Default | Description | |-------|------|---------|-------------| | agent_name | string | — | Unique agent identifier | | description | string | — | Agent purpose | | system_prompt | string | — | Behavior instructions | | model_name | string | gpt-4.1 | AI model (gpt-4o, claude-sonnet-4-20250514, etc.) | | role | string | worker | Agent role in swarm | | max_loops | int/string | 1 | Iterations ("auto" for autonomous) | | max_tokens | int | 8192 | Max response length | | temperature | float | 0.5 | Creativity (0.0–2.0) | | auto_generate_prompt | bool | false | Auto-enhance system prompt | | tools_list_dictionary | list | — | OpenAPI-style tool definitions | | streaming_on | bool | false | Enable SSE streaming | | mcp_url | string | — | MCP server URL | | selected_tools | list | all safe | Restrict available tools |

Rules

Always use environment variables for API keys — never hardcode.

Set appropriate max_loops — use "auto" only when sub-agent delegation is needed.

Match swarm_type to use case (see architecture table).

For streaming, set streaming_on: true and parse SSE events (metadata → chunks → usage → done).

Token launches cost ~0.04 SOL from the provided wallet.

Batch endpoint (/v1/swarm/batch/completions) requires Pro/Ultra/Premium tier.

Reasoning agents (/v1/reasoning-agent/completions) require Pro+ tier.

Resource Map

| Topic | Reference | |-------|-----------| | Full API architecture & tiers | references/architecture.md | | Sub-agent delegation patterns | references/sub-agents.md | | ATP payment protocol (Solana) | references/atp-protocol.md | | Marketplace publishing | references/marketplace.md | | Streaming implementation | references/streaming.md | | Tools integration | references/tools.md | | All docs pages | https://docs.swarms.ai/llms.txt |

Read references only when the task requires that specific depth.

Always use environment variables for API keys — never hardcode.

Set appropriate max_loops — use "auto" only when sub-agent delegation is needed.

Match swarm_type to use case (see architecture table).

For streaming, set streaming_on: true and parse SSE events (metadata → chunks → usage → done).

Token launches cost ~0.04 SOL from the provided wallet.

Batch endpoint (/v1/swarm/batch/completions) requires Pro/Ultra/Premium tier.

Reasoning agents (/v1/reasoning-agent/completions) require Pro+ tier.